Enhancing Metabolic Efficiency through Optimizing Metabolizable Protein Profile in a Time Progressive Manner with Weaned Goats as a Model: Involvement of Gut Microbiota

ABSTRACT Feeding a growing global population and lowering environmental pollution are the two biggest challenges facing ruminant livestock. Considering the significance of nitrogen metabolism in these challenges, a dietary intervention regarding metabolizable protein profiles with different rumen-undegradable protein (RUP) ratios (high RUP [HRUP] versus low RUP [LRUP]) was conducted in young ruminants with weaned goats as a model. Fecal samples were collected longitudinally for nine consecutive weeks to dissect the timing and duration of intervention, as well as its mechanism of action involving the gut microbiota. Results showed that at least 6 weeks of intervention were needed to distinguish the beneficial effects of HRUP, and HRUP intervention improved the metabolic efficiency of goats as evidenced by enhanced growth performance and nutrient-apparent digestibility at week 6 and week 8 after weaning. Integrated analysis of bacterial diversity, metabolites, and inferred function indicated that HRUP intervention promoted Eubacterium abundance, several pathways related to bacterial chemotaxis pathway, ABC transporters, and butanoate metabolism and thereafter elicited a shift from acetate production toward butyrate and branched-chain amino acid (BCAA) production. Meanwhile, three distinct phases of microbial progression were noted irrespective of dietary treatments, including the enrichment of fiber-degrading Ruminococcus, the enhancement of microbial cell motility, and the shift of fermentation type as weaned goats aged. The current report provides novel insights into early-life diet-microbiota axis triggered by metabolic protein intervention and puts high emphasis on the time window and duration of dietary intervention in modulating lifelong performance of ruminants. IMPORTANCE Precise dietary intervention in early-life gastrointestinal microbiota has significant implications in the long-life productivity and health of young ruminants, as well as in lowering their environmental footprint. Here, using weaned goats as a model, we report that animals adapted to high rumen-undegradable protein diet in a dynamic manner by enriching fecal community that could effectively move toward and scavenge nutrients such as glucose and amino acids and, thereafter, elicit butyrate and BCAA production. Meanwhile, the three dynamic assembly trajectories in fecal microbiota highlight the importance of taking microbiota dynamics into account. Our findings systematically reported when, which, and how the fecal microbiome responded to metabolizable protein profile intervention in young ruminants and laid a foundation for improving the productivity and health of livestock due to the host-microbiota interplay.

How big are the pens? Were they maintained in the pens during the digestibility measures? When were feed samples collected for what you analyzed in Table 1? Line 392: What time were the samples collected after feeding? The sampling time would affect microbial composition and metabolites. The authors provide a valuable study for precise feeding of goat by performing a series of time-scale experiments. Some findings from growth performance and metabolic phenotypes were very interesting. For example, Why HRUP can increase amino acid contents (i.e., Lys, His, Val, Phe in Table 2) in serum? It is surprising. High rumen undegradable protein diet (HRUP) remarkably improved the performance of goats (Fig.1). Why? These phenomena are very interesting. However, there is only weak supports from microbial analysis. So, it is necessary to improve microbial analysis for obtaining enough evidence supporting observed phenotypes. Some comments as followed for the improvement of MS.
1. Experimental diets (Table 1): how to define RUP and RDP based on the chemical composition of experimental diets? The observed differences of many compositions were shown in Table 1. It is very difficult to understand the contribution of HRUP or LRUP or to control the effect of non-protein compositions to all results. 2. In Fig.6, the observed pattern may be associated with goat development but not HRUPs or LRUPs. See Figure 2 (SCFA), Figure 3 (Microbial counts and proteins), and Figure 4, significant differences were observed between weeks but not between treatments, although the difference of alpha-diversity indices (Richness & Chao1) between treatments. Such difference may be due to the production of many singleton ASVs but not from diet changes. 3. Figure 5: the results are very interesting. Thus, how to link the results of 5B to three bacterial genera (Eubacterium, Faecalibacterium, and Bifidobacterium) in 5A? why not showing the progression of those three bacteria genera over time? It is crucial to determine their roles. In contrast, some other bacteria except for Bifidobacterium were shown in Figure 6C. It is confusing. Whether some metagenomic evidence can be provided to confirm the contributions of Eubacterium, Faecalibacterium, and Bifidobacterium to some distinct metabolic phenotypes. Here, it is unclear why only Eubacterium was highlighted in the graph in Figure 7 but exclude Faecalibacterium, and Bifidobacterium. 4. Figure 6: it is arbitrary to divide time points into three phases because no obvious pattern was observed, for example (6A), for HRUP treatment, a clear decrease occurred in wk4 and reached to the levels of wk7 and wk8. Correspondingly, in Figure 6C, most of bacterial genera did not show similar patterns like those in Figure 6A. Hence, please refine those results. 5. Fig.7 showed charming models or pathways but related evidence needs to be further strengthened. Here, there is overinterpretation for microbial analysis.

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Dear editors and reviewers,
Thanks for your letter and the reviewers' comments concerning our manuscript.
Those comments are all valuable and very helpful for revising and improving the readability and quality of our manuscript. We have studied these comments carefully and made modifications which we hope to meet with your approval in a point-to-point manner. Revised parts were marked using a red font in the manuscript.

Responses to Reviewer #1
Precise dietary intervention of nitrogen metabolism in early life has significant implications in the long-life productivity and health of young ruminants and lowering their environmental footprint. In the present study, Wu et al. investigated when, which and how the faecal microbiome responded to metabolizable protein profile intervention in young ruminants. The topic is of interest, the manuscript is well written and those findings have some significance for ruminant production, but some minor revisions should be done.
Reply: Thanks a lot for your positive and constructive comments. This manuscript has been revised substantially according to the reviewer's suggestions. All the revisions have been highlighted using a red font in the revised manuscript.
Line 380: How did you determine RDP and UDP?

Reply:
The RDP and RUP of these two diets were calculated based on the database of China feed ingredients (http://chinafeeddata.org.cn). Briefly, we queried the RDP and RUP content of each feed ingredient from the database, then calculated according to the ratio. Please see Lines 390-393 in the revised version.
Line 385: All the kid goats were weaned at 4 weeks old. Is it a normal strategy in goat production?
Reply: Thanks for your inquiry. In goat production, there are two ways of weaning strategies, i.e., early weaning and natural weaning. The natural weaning is prevalent for grazing ruminants, whereas early weaning (at 4 weeks) is usually carried out in intensive goat production to achieve economic and health benefits. Secondly, faeces were collected at the beginning of the formal trial, and then once a week (9 days). Moreover, in order to accurately measure the digestibility, fecal samples were collected every day in the sixth (7 consecutive days) and eighth (7 consecutive days) weeks. Therefore, faeces were totally collected 23 days. Please see [413][414][415] Thirdly, the feces and urine collection devices were composed of two parts, the upper net, which was used to collect faeces and the lower tray, which was used to collect urine. Throughout the experiment, kid goats were maintained in the pens and the size of the pen was 1.0 m × 1.2 m × 0.75 m (width × length × height). Please see

Reply:
The processing form of feed is powder. Please to see Line 388.

Responses to Reviewer #2
The authors provide a valuable study for precise feeding of goat by performing a series of time-scale experiments. Some findings from growth performance and metabolic phenotypes were very interesting. For example, Why HRUP can increase amino acid contents (i.e., Lys, His, Val, Phe in Table 2) in serum? It is surprising.
High rumen undegradable protein diet (HRUP) remarkably improved the performance of goats (Fig.1). Why? These phenomena are very interesting. However, there is only weak supports from microbial analysis. So, it is necessary to improve microbial analysis for obtaining enough evidence supporting observed phenotypes. Some comments as followed for the improvement of MS.
Reply: Thank you for your interest in this manuscript, as well as insightful and constructive comments. Please let us clarify in detail. Firstly, we observed interesting phenotypes that HRUP improved growth performance and nutrient apparent digestibility. A notable increase in branch-chain amino acid contents further suggested HRUP improved serum amino acid balance. Considering the significance of gut microbiota in host performance and health, we conducted integrated analysis of bacterial diversity, metabolites and their inferred function. Our findings systematically reported when, which and how the faecal microbiome responded to metabolizable protein profile intervention in young ruminants.
However, your detailed comments really helped us a lot in improving the MS. We have seriously thought about them and provided our detailed responses below. 2. In Fig.6, the observed pattern may be associated with goat development but not between treatments. Such difference may be due to the production of many singleton ASVs but not from diet changes.
Reply: Thanks for your inquiry and sorry to make you confused. Please let us clarify. Firstly, we have already removed singleton ASVs from the dataset since these singletons could be due to sequencing artefacts during microbial analysis, so such difference was not due to the production of many singleton ASVs. Please see Lines 466-467 in the revised manuscript.
Secondly, we cannot agree with you more that weeks might serve as the most significant driver for the SCFAs, microbial counts, MCPs and alpha-diversity indices.
Despite these, it is notable that HRUP drastically elevated the molar percentage of 3. Figure 5: the results are very interesting. Thus, how to link the results of 5B to three bacterial genera (Eubacterium, Faecalibacterium, and Bifidobacterium) in 5A? why not showing the progression of those three bacteria genera over time? It is crucial to determine their roles. In contrast, some other bacteria except for Bifidobacterium were shown in Figure 6C. It is confusing. Whether some metagenomic evidence can be provided to confirm the contributions of Eubacterium, Faecalibacterium, and Bifidobacterium to some distinct metabolic phenotypes. Here, it is unclear why only Eubacterium was highlighted in the graph in Figure 7 but exclude Faecalibacterium, and Bifidobacterium.
Reply: Thanks for your constructive comments. Good point! Firstly, sorry to make you confused. Those three bacteria genera in Fig.5A were landmark differential bacteria caused by treatments. Some landmark differential bacteria in Fig.6C were identified at different time periods in both groups. However, according to your suggestions, we have added Eubacterium and Faecalibacterium in Fig.6C to show the progression of those three bacteria genera over time. Thereafter, we added relevant information in the manuscript. Please see [229][230][231][232][233][234][338][339] in the revised version.
Secondly, in respect to why only Eubacterium was highlighted in the graph in Figure 7, please let us explain. We cannot agree with you more that further metagenomic evidence could assist in explaining the contribution of gut microbiota to distinct metabolic phenotypes. This validation work is in progress and more powerful data will be provided in the future. Despite these, in the current work, inferred microbial function and metabolite analysis based on SCFA profile both confirmed that HRUP treatment enhanced butyrate production. It is generally accepted that Bifidobacterium was associated with gut lactate and formate production, while not butyrate production. Meanwhile, although gut microbes belonging to Eubacterium and Faecalibacterium possessed the capacity to produce butyrate, only Eubacterium abundance was enhanced by HRUP treatment. Therefore, it is plausible to infer that the enrichment of Eubacterium by HRUP treatment contributed most to the metabolic phenotypes characterized by enhanced butyrate production; and only Eubacterium was highlighted in the graph in Figure 7. These information have been added in the revised manuscript, please see Lines 184-187.
If you have further inquiry, we are happy to answer.
4. Figure 6: it is arbitrary to divide time points into three phases because no obvious pattern was observed, for example (6A), for HRUP treatment, a clear decrease occurred in wk4 and reached to the levels of wk7 and wk8. Correspondingly, in Figure 6C, most of bacterial genera did not show similar patterns like those in Figure   6A. Hence, please refine those results.

Reply:
We thank the referee for this valuable suggestion and apologize for the unclear description. Firstly, the three distinct phases were divided based on betweengroup (Fig.4B) and within-group (Fig.6A) bray curtis distance. On one hand, the pairwise PERANOMA analysis indicated that bacterial diversity in the early (wk0-2), middle (wk3-5) and late phase (wk 6-8) was different from each other (P < 0.01, Fig.4B). On the other hand, a wave crest appeared in within-group dissimilarity during middle phase, where the Bray-Curtis dissimilarity among different individuals within each week was the highest, greater than those in early and late phases (P < 0.05, Fig.6A).
Secondly, Fig.6A showed the within-group bray curtis dissimilarity, while Fig.   6C showed progression of specific bacterial genera over week. In the revised Fig. 6C, five genera were prevalent in the early phase, while three genera dominated the late phase. Hence, they did not show similar patterns.
All those results were refined in the revised version. Please see Lines 218-226. If you have further suggestions, we are happy to follow. 5. Fig.7 showed charming models or pathways but related evidence needs to be further strengthened. Here, there is over-interpretation for microbial analysis.

Reply:
We really appreciated for the reviewer's valuable and earnest comment. It is of particular importance to further validate and increased the power of our data through omics-based, culture-based or transplantation-based of intestinal microbiota.
We cannot agree you with more that there is a little over-interpretation for microbial analysis. Hence, we preferred to keep Fig.7, while added some relevant information to Your manuscript has been accepted, and I am forwarding it to the ASM Journals Department for publication. You will be notified when your proofs are ready to be viewed.
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